Harvesting is one of the most challenging tasks in fruit production. Robotic fruit harvesting technologies are being studied because of labor-intensive and costly handpicking. Due to the unstructured and dynamic characteristics of both the target fruit and its surrounding environment, current harvesting robots have limited performance. Therefore, the commercial applications of most fruit harvesting robots are unrealized. The application and research progress of fruit harvesting robots in apple and kiwifruit harvesting have been reported in this chapter. The applications and development of fruit detection and end-effector design for complex orchard are focused. The main methods used in fruit detection are reviewed, including single feature detection methods, multi-features fusion detection methods, deep learning methods, and 3D reconstruction methods. The technology of end-effector design for selective harvesting with apple and kiwifruit, and shake-and-catch mechanism for bulk harvesting with apple are also reviewed. Existing research problems of fruit harvesting robots in robotic harvesting applications are mentioned, and future development directions of agriculture robots are described.